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《Journal of Zhejiang University(Engineering Science)》 2007-09
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Adaptive wavelet thresholding based ultrasonic signal denoising

LIU Shou-shan,YANG Chen-long,LI Ling,ZHOU Xiao-jun(College of Mechanical and Energy Engineering,Zhejiang University,Hangzhou 310027,China)  
A model of ultrasonic flaw echo detection was built to depress the high scattering microstructure noise in the ultrasonic signal from aluminum alloy forge.A new wavelet thresholding function based Stein unbiased risk estimation method was set up to perform the adaptive denoising procedure.The discrete wavelet coefficients of different scale were calculated by using the new thresholding function,then a thresholds iterative process based on the minimum mean square error was implemented.The new estimated signal was rebuilt though wavelet inverse transform by using the calculated wavelet coefficients.The iterative process would be continued until the terminated condition was accessed.The processing results of the ultrasonic signals with flaw from aluminum alloy forge indicates that compared to the other denoising methods based on the standard hard thresholding and soft thresholding functions,the adaptive denoising method has better denoising performance on the microstructure noise and can enhance the flaw echo signal.
【CateGory Index】: TB553
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